Aplicações de métodos de classificação e calibração multivariada acoplados com técnicas espectroscópicas em amostras ambientais e alimentos

Este trabalho de pesquisa descreve dois estudos de caso de métodos quimiométricos empregados para a quantificação de hidrocarbonetos policíclicos aromáticos HPAs (naftaleno, fluoreno, fenantreno e fluoranteno) em água potável usando espectroscopia de fluorescência molecular e a classificação e caracterização de sucos de uva e seus parâmetros de qualidade através de espectroscopia de infravermelho próximo. O objetivo do primeiro estudo é a aplicação combinada de métodos quimiométricos de segunda ordem (N-PLS, U-PLS, U-PLS/RBL e PARAFAC) e espectrofluorimetria para determinação direta de HPAs em água potável, visando contribuir para o conhecimento do potencial destas metodologias como alternativa viável para a determinação tradicional por cromatografia univariada. O segundo estudo de caso destinado à classificação e determinação de parâmetros de qualidade de sucos de uva, densidade relativa e teor de sólidos solúveis totais, foi medida por espectroscopia de infravermelho próximo e métodos quimiométricos. Diversos métodos quimiométricos, tais como HCA, PLS-DA, SVM-DA e SIMCA foram investigados para a classificação amostras de sucos de uva ao mesmo tempo que métodos de calibração multivariada de primeira ordem, tais como PLS, iPLS e SVM-LS foram usadas para a predição dos parâmetros de qualidade. O princípio orientador para o desenvolvimento dos estudos aqui descritos foi a necessidade de metodologias analíticas com custo, tempo de execução e facilidade de operação melhores e menor produção de resíduos do que os métodos atualmente utilizados para a quantificação de HPAs, em água de torneira, e classificação e caracterização das amostras de suco de uva e seus parâmetros de qualidade

Acoplamento de técnicas espectrométricas com métodos quimiométricos de classificação e calibração multivariada em alimentos

Este trabalho de pesquisa descreve três estudos de utilização de métodos quimiométricos para a classificação e caracterização de óleos comestíveis vegetais e seus parâmetros de qualidade através das técnicas de espectrometria de absorção molecular no infravermelho médio com transformada de Fourier e de espectrometria no infravermelho próximo, e o monitoramento da qualidade e estabilidade oxidativa do iogurte usando espectrometria de fluorescência molecular. O primeiro e segundo estudos visam à classificação e caracterização de parâmetros de qualidade de óleos comestíveis vegetais utilizando espectrometria no infravermelho médio com transformada de Fourier (FT-MIR) e no infravermelho próximo (NIR). O algoritmo de Kennard-Stone foi usado para a seleção do conjunto de validação após análise de componentes principais (PCA). A discriminação entre os óleos de canola, girassol, milho e soja foi investigada usando SVM-DA, SIMCA e PLS-DA. A predição dos parâmetros de qualidade, índice de refração e densidade relativa dos óleos, foi investigada usando os métodos de calibração multivariada dos mínimos quadrados parciais (PLS), iPLS e SVM para os dados de FT-MIR e NIR. Vários tipos de pré-processamentos, primeira derivada, correção do sinal multiplicativo (MSC), dados centrados na média, correção do sinal ortogonal (OSC) e variação normal padrão (SNV) foram utilizados, usando a raiz quadrada do erro médio quadrático de validação cruzada (RMSECV) e de predição (RMSEP) como parâmetros de avaliação. A metodologia desenvolvida para determinação de índice de refração e densidade relativa e classificação dos óleos vegetais é rápida e direta. O terceiro estudo visa à avaliação da estabilidade oxidativa e qualidade do iogurte armazenado a 4C submetido à luz direta e mantido no escuro, usando a análise dos fatores paralelos (PARAFAC) na luminescência exibida por três fluoróforos presentes no iogurte, onde pelo menos um deles está fortemente relacionado com as condições de armazenamento. O sinal fluorescente foi identificado pelo espectro de emissão e excitação das substâncias fluorescentes puras, que foram sugeridas serem vitamina A, triptofano e riboflavina. Modelos de regressão baseados nos escores do PARAFAC para a riboflavina foram desenvolvidos usando os escores obtidos no primeiro dia como variável dependente e os escores obtidos durante o armazenamento como variável independente. Foi visível o decaimento da curva analítica com o decurso do tempo da experimentação. Portanto, o teor de riboflavina pode ser considerado um bom indicador para a estabilidade do iogurte. Assim, é possível concluir que a espectroscopia de fluorescência combinada com métodos quimiométricos é um método rápido para monitorar a estabilidade oxidativa e a qualidade do iogurte

Measurement of polycyclic aromatic hydrocarbons in ambient air by fluorescence spectroscopic techniques

250 p. + anexos

Aplicações de métodos quimiométricos e de técnicas analíticas em amostras alimentícias e farmacêuticas

Esse trabalho compreende dois diferentes estudos de caso: o primeiro foi a respeito de um medicamento para o qual foi desenvolvida uma metodologia para determinar norfloxacino (NOR) por espectrofluorimetria molecular e validação por HPLC. Primeiramente foi desenvolvida uma metodologia por espectrofluorimetria onde foram feitos alguns testes preliminares a fim de estabelecer qual valor de pH iria fornecer a maior intensidade de emissão. Após fixar o pH foi feita a determinação de NOR em padrões aquosos e soluções do medicamento usando calibração univariada. A faixa de concentração trabalhada foi de 0500 μg.L-1. O limite de detecção para o medicamento foi de 6,9 μg.L-1 enquanto que o de quantificação foi de 24,6 μg.L-1. Além dessas, outras figuras de mérito também foram estimadas para desenvolvimento da metodologia e obtiveram resultados muito satisfatórios, como por exemplo, os testes de recuperação no qual a recuperação do analito foi de 99.5 a 103.8%. Para identificação e quantificação do NOR da urina foi necessário diluir a amostra de urina (estudada em dois diferentes níveis de diluição: 500 e 1000 x) e também uso do método da adição de padrão (na mesma faixa de concentração usada para medicamento). Após a aquisição do espectro, todos foram usados para construção do tensor que seria usado no PARAFAC. Foi possível estimar as figuras de mérito como limite de detecção de 11.4 μg.L-1 and 8.4 μg.L-1 (diluição de 500 e 1000 x respectivamente) e limite de quantificação de 34 μg.L-1 e 25.6 μg.L-1 (diluição de 500 x e 1000 x respectivamente). O segundo estudo de caso foi na área alimentícia no qual se usou espectroscopia NIR e FT MIR acopladas a quimiometria para discriminar óleo de soja transgênica e não transgênica. Os espectros dos óleos não mostraram diferença significativa em termos visuais, sendo necessário usar ferramentas quimiométricas capazes de fazer essa distinção. Tanto para espectroscopia NIR quanto FT MIR foi feito o PCA a fim de identificar amostras discrepantes e que influenciariam o modelo de forma negativa. Após efetuar o PCA, foram usadas três diferentes técnicas para discriminar os óleos: SIMCA, SVM-DA e PLS-DA, sendo que para cada técnica foram usados também diferentes pré processamento. No NIR, apenas para um pré processamento se obteve resultados satisfatórios nas três técnicas, enquanto que para FT-MIR ao se usar PLS-DA se obteve 100% de acerto na classificação para todos os pré processamentos

Comprehensive two-dimensional gas chromatography combined to multivariate data analysis for detection of disease-resistant clones of Eucalyptus

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Metabolic profiling by ultra-performance liquid chromatography-mass spectrometry and parallel factor analysis for the determination of disease biomarkers in Eucalyptus

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Multivariate spectroscopic methods for the analysis of solutions

In this thesis some multivariate spectroscopic methods for the analysis of solutions are proposed. Spectroscopy and multivariate data analysis form a powerful combination for obtaining both quantitative and qualitative information and it is shown how spectroscopic techniques in combination with chemometric data evaluation can be used to obtain rapid, simple and efficient analytical methods. These spectroscopic methods consisting of spectroscopic analysis, a high level of automation and chemometric data evaluation can lead to analytical methods with a high analytical capacity, and for these methods, the term high-capacity analysis (HCA) is suggested. It is further shown how chemometric evaluation of the multivariate data in chromatographic analyses decreases the need for baseline separation. The thesis is based on six papers and the chemometric tools used are experimental design, principal component analysis (PCA), soft independent modelling of class analogy (SIMCA), partial least squares regression (PLS) and parallel factor analysis (PARAFAC). The analytical techniques utilised are scanning ultraviolet-visible (UV-Vis) spectroscopy, diode array detection (DAD) used in non-column chromatographic diode array UV spectroscopy, high-performance liquid chromatography with diode array detection (HPLC-DAD) and fluorescence spectroscopy. The methods proposed are exemplified in the analysis of pharmaceutical solutions and serum proteins. In Paper I a method is proposed for the determination of the content and identity of the active compound in pharmaceutical solutions by means of UV-Vis spectroscopy, orthogonal signal correction and multivariate calibration with PLS and SIMCA classification. Paper II proposes a new method for the rapid determination of pharmaceutical solutions by the use of non-column chromatographic diode array UV spectroscopy, i.e. a conventional HPLC-DAD system without any chromatographic column connected. In Paper III an investigation is made of the ability of a control sample, of known content and identity to diagnose and correct errors in multivariate predictions something that together with use of multivariate residuals can make it possible to use the same calibration model over time. In Paper IV a method is proposed for simultaneous determination of serum proteins with fluorescence spectroscopy and multivariate calibration. Paper V proposes a method for the determination of chromatographic peak purity by means of PCA of HPLC-DAD data. In Paper VI PARAFAC is applied for the decomposition of DAD data of some partially separated peaks into the pure chromatographic, spectral and concentration profiles.

Machine Learning applicato al Web Semantico: Statistical Relational Learning vs Tensor Factorization

Obiettivo della tesi è analizzare e testare i principali approcci di Machine Learning applicabili in contesti semantici, partendo da algoritmi di Statistical Relational Learning, quali Relational Probability Trees, Relational Bayesian Classifiers e Relational Dependency Networks, per poi passare ad approcci basati su fattorizzazione tensori, in particolare CANDECOMP/PARAFAC, Tucker e RESCAL.

Dissolved organic matter in the Lena River Delta Region, Siberia, Russia

Connectivity between the terrestrial and marine environment in the Artic is changing as a result of climate change, influencing both freshwater budgets and the supply of carbon to the sea. This study characterizes the optical properties of dissolved organic matter (DOM) within the Lena Delta region and evaluates the behavior of DOM across the fresh water-marine gradient. Six fluorescent components (four humic-like; one marine humic-like; one protein-like) were identified by Parallel Factor Analysis (PARAFAC) with a clear dominance of allochthonous humic-like signals. Colored DOM (CDOM) and dissolved organic carbon (DOC) were highly correlated and had their distribution coupled with hydrographical conditions. Higher DOM concentration and degree of humification were associated with the low salinity waters of the Lena River. Values decreased towards the higher salinity Laptev Sea shelf waters. Results demonstrate different responses of DOM mixing in relation to the vertical structure of the water column, as reflecting the hydrographical dynamics in the region. Two mixing curves for DOM were apparent. In surface waters above the pycnocline there was a sharper decrease in DOM concentration in relation to salinity indicating removal. In the bottom water layer the DOM decrease within salinity was less. We propose there is a removal of DOM occurring primarily at the surface layer, which is likely driven by photodegradation and flocculation.

A metabolomic approach to study the rhizodeposition in the tritrophic interaction: tomato, Pochonia chlamydosporia and Meloidogyne javanica

A combined chemometrics-metabolomics approach [excitation–emission matrix (EEM) fluorescence spectroscopy, nuclear magnetic resonance (NMR) and high performance liquid chromatography–mass spectrometry (HPLC–MS)] was used to analyse the rhizodeposition of the tritrophic system: tomato, the plant-parasitic nematode Meloidogyne javanica and the nematode-egg parasitic fungus Pochonia chlamydosporia. Exudates from M. javanica roots were sampled at root penetration (early) and gall development (late). EMM indicated that late root exudates from M. javanica treatments contained more aromatic amino acid compounds than the rest (control, P. chlamydosporia or P. chlamydosporia and M. javanica). 1H NMR showed that organic acids (acetate, lactate, malate, succinate and formic acid) and one unassigned aromatic compound (peak no. 22) were the most relevant metabolites in root exudates. Robust principal component analysis (PCA) grouped early exudates for nematode (PC1) or fungus presence (PC3). PCA found (PC1, 73.31 %) increased acetate and reduced lactate and an unassigned peak no. 22 characteristic of M. javanica root exudates resulting from nematode invasion and feeding. An increase of peak no. 22 (PC3, 4.82 %) characteristic of P. chlamydosporia exudates could be a plant “primer” defence. In late ones in PC3 (8.73 %) the presence of the nematode grouped the samples. HPLC–MS determined rhizosphere fingerprints of 16 (early) and 25 (late exudates) m/z signals, respectively. Late signals were exclusive from M. javanica exudates confirming EEM and 1H NMR results. A 235 m/z signal reduced in M. javanica root exudates (early and late) could be a repressed plant defense. This metabolomic approach and other rhizosphere -omics studies could help to improve plant growth and reduce nematode damage sustainably.

Multivariate monitoring of a biological wastewater treatment process: a case study at Melbourne Water's Western Treatment Plant

Biological wastewater treatment is a complex, multivariate process, in which a number of physical and biological processes occur simultaneously. In this study, principal component analysis (PCA) and parallel factor analysis (PARAFAC) were used to profile and characterise Lagoon 115E, a multistage biological lagoon treatment system at Melbourne Water's Western Treatment Plant (WTP) in Melbourne, Australia. In this study, the objective was to increase our understanding of the multivariate processes taking place in the lagoon. The data used in the study span a 7-year period during which samples were collected as often as weekly from the ponds of Lagoon 115E and subjected to analysis. The resulting database, involving 19 chemical and physical variables, was studied using the multivariate data analysis methods PCA and PARAFAC. With these methods, alterations in the state of the wastewater due to intrinsic and extrinsic factors could be discerned. The methods were effective in illustrating and visually representing the complex purification stages and cyclic changes occurring along the lagoon system. The two methods proved complementary, with each having its own beneficial features. (C) 2003 Elsevier B.V. All rights reserved.

Analysis of lipoproteins using 2D diffusion-edited NMR spectroscopy and multi-way chemometrics

This study represents the first application of multi-way calibration by N-PLS and multi-way curve resolution by PARAFAC to 2D diffusion-edited H-1 NMR spectra. The aim of the analysis was to evaluate the potential for quantification of lipoprotein main- and subtractions in human plasma samples. Multi-way N-PLS calibrations relating the methyl and methylene peaks of lipoprotein lipids to concentrations of the four main lipoprotein fractions as well as 11 subfractions were developed with high correlations (R = 0.75-0.98). Furthermore, a PARAFAC model with four chemically meaningful components was calculated from the 2D diffusion-edited spectra of the methylene peak of lipids. Although the four extracted PARAFAC components represent molecules of sizes that correspond to the four main fractions of lipoproteins, the corresponding concentrations of the four PARAFAC components proved not to be correlated to the reference concentrations of these four fractions in the plasma samples as determined by ultracentrifugation. These results indicate that NMR provides complementary information on the classification of lipoprotein fractions compared to ultracentrifugation. (C) 2004 Elsevier B.V. All rights reserved.

Tíz év az Európai Unióban - az új tagországok agrárteljesítményei = A decade in the EU: the agricultural performances of the new member-states

Több mint tíz év telt el az Európai Unió 2004. évi kibővülése óta. A tízéves évforduló jó lehetőséget kínált a mérlegkészítésre, annak vizsgálatára, hogy a legfrissebb elérhető adatok tükrében milyen fejlődési pályát tudhatnak maguk mögött az új tagországok mezőgazdasági szektorai. Írásunk célja a tíz kelet- európai EU-tagállam agrárteljesítményének értékelése, illetve ez alapján a csatlakozás nyerteseinek, illetve veszteseinek azonosítása. A rendelkezésre álló adatokat a többdimenziós faktoranalízis módszerével feldolgozva arra az eredményre jutottunk, hogy Lengyelország, Észtország és Litvánia hármasa tekinthető az agrárcsatlakozás abszolút nyertesének, míg a többi új tagállam nem volt képes teljes mértékben kihasználni a csatlakozás adta lehetőségeket. Az eredményekből az is látható, hogy a magas hozzáadott értékű termékekre való szakosodás jó stratégiának bizonyult, mert gyorsabb fejlődést biztosított, mint a mezőgazdasági alaptermékekre való koncentrálás. ____ The period of over ten years since the 2004 round of EU accessions provides a good opportunity to assess and take stock of agricultural developments in the new member- States, in light of the latest available data. The paper sets out to assess their agricultural performances and to identify the winners and losers by accession in this regard. Ranking individual country performances using Parallel Factor Analysis (PARAFAC) suggests that Poland, Estonia and Lithuania can be considered as winners, whereas the other countries failed to use the potentials of membership to the full. The results also suggest that focusing on agri-food products with a high added value proved a good development strategy for the sector. Countries that concentrated on producing agri-food raw materials lagged behind.

Large scale data processing using MapReduce

As massive data sets become increasingly available, people are facing the problem of how to effectively process and understand these data. Traditional sequential computing models are giving way to parallel and distributed computing models, such as MapReduce, both due to the large size of the data sets and their high dimensionality. This dissertation, as in the same direction of other researches that are based on MapReduce, tries to develop effective techniques and applications using MapReduce that can help people solve large-scale problems. Three different problems are tackled in the dissertation. The first one deals with processing terabytes of raster data in a spatial data management system. Aerial imagery files are broken into tiles to enable data parallel computation. The second and third problems deal with dimension reduction techniques that can be used to handle data sets of high dimensionality. Three variants of the nonnegative matrix factorization technique are scaled up to factorize matrices of dimensions in the order of millions in MapReduce based on different matrix multiplication implementations. Two algorithms, which compute CANDECOMP/PARAFAC and Tucker tensor decompositions respectively, are parallelized in MapReduce based on carefully partitioning the data and arranging the computation to maximize data locality and parallelism.

Characterization, sources, and transformations of dissolved organic matter (DOM) in Florida coastal Everglades (FCE)

Dissolved organic matter (DOM) is one of the largest carbon reservoirs on this planet and is present in aquatic environments as a highly complex mixture of organic compounds. The Florida coastal Everglades (FCE) is one of the largest wetlands in the world. DOM in this system is an important biogeochemical component as most of the nitrogen (N) and phosphorous (P) are in organic forms. Achieving a better understanding of DOM dynamics in large coastal wetlands is critical, and a particularly important issue in the context of Everglades restoration. In this work, the environmental dynamics of surface water DOM on spatial and temporal scales was investigated. In addition, photo- and bio-reactivity of this DOM was determined, surface-to-groundwater exchange of DOM was investigated, and the size distribution of freshwater DOM in Everglades was assessed. The data show that DOM dynamics in this ecosystem are controlled by both hydrological and ecological drivers and are clearly different on spatial scales and variable seasonally. The DOM reactivity data, modeled with a multi-pool first order degradation kinetics model, found that fluorescent DOM in FCE is generally photo-reactive and bio-refractory. Yet the sequential degradation proved a “priming effect” of sunlight on the bacterial uptake and reworking of this subtropical wetland DOM. Interestingly, specific PARAFAC components were found to have different photo- and bio-degradation rates, suggesting a highly heterogeneous nature of fluorophores associated with the DOM. Surface-to-groundwater exchange of DOM was observed in different regions of the system, and compositional differences were associated with source and photo-reactivity. Lastly, the high degree of heterogeneity of DOM associated fluorophores suggested based on the degradation studies was confirmed through the EEM-PARAFAC analysis of DOM along a molecular size continuum, suggesting that the fluorescence characteristics of DOM are highly controlled by different size fractions and as such can exhibit significant differences in reactivity.